numerous studies yet have been carried out on downscaling of the large-scale climate data usingboth dynamical and statistical methods to investigate the hydrological and meteorological impacts of climatechange on different parts of the world. this study was also conducted to investigate the capability of feedforwardneural network with error back-propagation algorithm to downscale the provincial...

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...

Neural networks have been used successfully to a broad range of areas such as business, data mining, drug discovery and biology. In medicine, neural networks have been applied widely in medical diagnosis, detection and evaluation of new drugs and treatment cost estimation. In addition, neural networks have begin practice in data mining strategies for the aim of prediction, knowledge discovery. ...

The estimation of pollution fields, especially in densely populated areas, is an important application in the field of environmental science due to the significant effects of air pollution on public health. In this paper, we investigate the spatial distribution of three air pollutants in Tehran’s atmosphere: carbon monoxide (CO), nitrogen dioxide (NO2), and atmospheric particulate matters less ...

PMC13 ESTIMATING COST-OF-ILLNESS USING GENERALIZED LINEAR MODELS: AN ALTERNATIVETOTHE SMEARING APPROACH Exuzides A, Colby C, Spalding JR ICON Clinical Research, San Francisco, CA, USA, Astellas Pharma US, Deerfield, IL, USA OBJECTIVES: Estimation of cost-of-illness typically involves the analysis of skewed medical costs that include large outliers. Log transformations are frequently used to ove...

The main objective of this study was to develop a hybrid neuro-fuzzy system for estimating the magnitude of EMG responses of 10 trunk muscles based on two lifting task variables (trunk velocity and trunk moment) as model inputs. The input and output variables were represented using the fuzzy membership functions. The initial fuzzy rules were generated by the neural network using true EMG data. ...

Abstract In this study, the CCHE2D model was used to analyze flow patterns in Tigris River Baghdad city around a water treatment plant. To end, calibrated and validated steady-state using relevant boundary conditions. The initial surface level at Sarai station for three discharges of 289, 530, 870 m 3 /s. Hence, appropriate manning roughness modulus equivalent mixing length turbulent models wer...

soil hydraulic properties such as soil water characteristic curve are necessary prerequisite for modeling water movement and solute transport. direct methods of estimating these hydraulic properties are time consuming and costly. indirect methods, such as pedotransfer functions, estimate the hydraulic parameters using easy-to-measure soil properties like particle size distributions, bulk densit...

BACKGROUND Generalized linear models (GLMs) have recently been introduced into cost data analysis. GLMs, transformations of the linear regression model, are characterized by a particular response distribution from one of the exponential family of distributions and monotonic link function which relates the response mean to a scale on which additive model effects operate. OBJECTIVES This study ...